Urban microclimates have a great impact on the thermal comfort of city inhabitants, with the Urban Heat Island (UHI) and the Subsurface Urban Heat Island (SUHI) effects posing a growing challenge under the accelerating impacts of climate change. This thesis focuses on investigating the UHI and SUHI effects and exploring potential mitigation strategies within a controlled urban environment, specifically the ”Heat Square” at The Green Village in the Delft University of Technology. The Heat Square serves as an experimental urban environment designed to analyse various urban cooling measures. To capture the spatial and temporal variations in soil temperature within the Heat Square, Distributed Temperature Sensing (DTS) technology was deployed. DTS measures high-resolution temperature data, which allows for detailed analysis of the soil temperature response to different cooling scenarios, including the implementation of green infrastructure, shading, and reflective surfaces. These in-situ measurements were then compared with urban microclimate modeling results using ENVI-met, a Computational Fluid Dynamics (CFD) tool for modeling urban microclimatic conditions. ENVI-met, along with other urban microclimate models, can predict the impact of urban design on local temperature and thermal comfort indices. The findings of this research highlight the significant potential of green infrastructure and shading as effective strategies to mitigate the UHI effect. Specifically, the introduction of vegetation and shading elements resulted in noticeable reductions in both surface and air temperatures as well as Mean Radiant Temperature (Tmrt) within the urban environment. These findings were supported by performing simulations of different urban scenarios of the Heat Square. However, the study also highlighted challenges in accurately modeling urban microclimates, as shown by discrepancies between the DTS measurements and ENVI-met simulations. These differences suggest the need for further refinement of model parameters to better approximate the complexities of real-world urban environments. Overall, this thesis contributes to the broader understanding of urban cooling measures and their role in enhancing the resilience of cities to climate change. The insights gained from this research are intended to inform urban planning and design practices, promoting the development of more sustainable and climate-resilient urban spaces as well as the applicability of urban microclimate monitoring tools. Future research should focus on refining the ENVI-met model of the Heat Square to enhance its accuracy in properly simulation real-life responses of the urban environment to climatic variations. Additionally, exploring a broader range of urban cooling strategies, including water-based solutions and varying surface materials, could broaden knowledge on heat mitigation strategies. Studying soil thermal responses in other urban environments with DTS would also be valuable for studying indirect effects of the SUHI effect. Collaborations between researchers, urban planners, and policymakers are important to ensure that scientific findings are translated into practical applications that increase climate adaptability of urban environments.

This report provides a flood risk assessment of the Isiolo River Basin, in collaboration with Nelen & Schuurmans (3Di, FIS Tool) and Zephyr Consulting (SLAMDAM). This flood risk assessment includes a study of the current flood risk management in Kenya, and in the Isiolo River Basin in particular, because the need for proper flood management is urgent: various climate studies predict an increase in rainfall and an increase in flood risk as a result of the effects of climate change.

Current flood risk management is inadequate. Kenya has defined 21 flood-prone areas whereof one of them is Isiolo Town. Isiolo Town is located in the ENN basin which is, relatively, the most prone to the effects of climate change compared to the other basins. Furthermore, the ENN basin currently has the highest poverty rate and avoidance of further enlargement in poverty rate is important, so there is a need to mitigate flood risks. Since Isiolo Town is located in the Isiolo River Basin, this basin has been chosen for an in-depth study.

The Isiolo River Basin is an Arid Semi-Arid Land region which is often prone to flash floods. Isiolo Town is a flat area located downstream of mountainous area, the rain which falls upstream flows fast downstream and converges into town, often resulting in inundation. Many hazards, both natural and others, are increasing the flood risk in the basin and specifically Isiolo Town.

This flood risk demands flood risk mitigation measures. One possible measure is the SLAMDAM. The SLAMDAM is a movable water-filled flood-barrier. One dam has a length of 5 meters and a height of 1 meter and the dams can be connected to a desired length. The water stored in the dam can be used afterwards for irrigation or other uses.
To recommend effective areas to implement the SLAMDAM, 3Di and the FIS Tool are used. 3Di is a hydrodynamic model and it creates flood maps for different rain events. These flood maps are used as input for the FIS Tool. The FIS Tool calculates the benefits for deploying the SLAMDAM at a certain location for a particular length. The locations which result in the highest benefit are recommended to deploy the SLAMDAM in case of particular rain events. However, a site visit is required to see whether the modelled situation aligns with the real-life situation and to see whether boundary conditions are met.
The SLAMDAM is also compared to other flood risk mitigation measures. Some were analysed using the FIS Tool, whereas others are evaluated based on five self-formulated ranking criteria. These criteria form the base of a scoring matrix where each relevant mitigation measure is scored on.

The performed research has shown the SLAMDAM to rank the best compared to other mitigation measures, both when using the scoring matrix and when using the FIS Tool. However, it is highly recommended to use the SLAMDAM in combination with a Flood Early Warning System. In this way the community downstream can be warned in time to deploy the SLAMDAM. The FIS Tool is found to be especially valuable in finding proper locations for deployment and the dam can be stored close to these locations, enabling fast deployment of the dam in case of need.